Predicting the risk of 7‐day readmission in late preterm infants in California: A population‐based cohort study

Abstract Background and aims The American Academy of Pediatrics describes late preterm infants, born at 34 to 36 completed weeks' gestation, as at‐risk for rehospitalization and severe morbidity as compared to term infants. While there are prediction models that focus on specific morbidities, there is limited research on risk prediction for early readmission in late preterm infants. The aim of this study is to derive and validate a model to predict 7‐day readmission. Methods This is a population‐based retrospective cohort study of liveborn infants in California between January 2007 to December 2011. Birth certificates, maintained by California Vital Statistics, were linked to a hospital discharge, emergency department, and ambulatory surgery records maintained by the California Office of Statewide Health Planning and Development. Random forest and logistic regression were used to identify maternal and infant variables of importance, test for association, and develop and validate a predictive model. The predictive model was evaluated for discrimination and calibration. Results We restricted the sample to healthy late preterm infants (n = 122,014), of which 4.1% were readmitted to hospital within 7‐day after birth discharge. The random forest model with 24 variables had better predictive ability than the 8 variable logistic model with c‐statistic of 0.644 (95% confidence interval 0.629, 0.659) in the validation data set and Brier score of 0.0408. The eight predictors of importance length of stay, delivery method, parity, gestational age, birthweight, race/ethnicity, phototherapy at birth hospitalization, and pre‐existing or gestational diabetes were used to drive individual risk scores. The risk stratification had the ability to identify an estimated 19% of infants at greatest risk of readmission. Conclusions Our 7‐day readmission predictive model had moderate performance in differentiating at risk late preterm infants. Future studies might benefit from inclusion of more variables and focus on hospital practices that minimize risk.


| INTRODUCTION
Readmission within 30-day after index admission is used as a quality-ofcare measure in adult medicine. 1,2 However, the appropriateness of the 30-day cutoff for pediatric patients is controversial. Early readmission, defined as readmission within 7-day from discharge, is preferred to approximate preventability. 3 In the neonatal period, late preterm infants (LPTs), born at 34 to 36 completed weeks' gestation, are at two-to-threefold increased risk of readmission after birth as compared to term infants. 4,5 The majority of these readmissions occur shortly after birth discharge and are primarily due to hyperbilirubinemia, feeding difficulties, infection/sepsis, or respiratory complications. [5][6][7] Efforts taken to minimize the risk of unplanned early readmission, such as longer length of birth hospitalization, have mixed outcomes; 8 predischarge bilirubin screening and subthreshold phototherapy during birth hospitalization have shown promise, however, the number needed to treat is large. 9,10 Differentiating those who are at increased risk of unplanned early readmission following birth hospitalization could potentially inform targeted predischarge care and transition planning.
Previous studies have identified factors that may be useful for such differentiation including length of stay at birth hospitalization, gestational age, and predischarge bilirubin screening. 5 indicating a transfer to another hospital were identified as "transferred" and those whose birth admission discharge status indicated death as "died during birth hospitalization." California birth certificates include a variable that indicates if an infant was admitted to a neonatal intensive care unit (NICU). By excluding LPTs who were transferred, died, admitted to a NICU during birth hospitalization, or had major congenital anomalies, 13 we aimed to limit the sample to those presumed healthy at birth hospitalization. Information on diagnosis was based on the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9) and International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10). 14 A complete case analysis was performed, as missing data for predictor variables of interest were minimal (<3%).

| Outcome
The outcome of interest, readmission within 7-day, was defined as any LPTs readmitted to hospital within 7-day after birth hospitalization.

| Predictor variables
Biological plausibility, accuracy in measurement, availability in the database, and reliability of record were criteria applied by the study team to narrow the list of candidate variables from 34 (identified a priori based on literature) to 24 (Supporting Information: eTable 1). The candidate variables included maternal and infant characteristics, maternal and infant morbidity, and healthcare payor. Our database had limited infant morbidity variables and the disease conditions, though identified in literature as contributing to readmission in preterm infants, that were available to us were mostly prevalent in early preterm infants.

| Statistical analysis
A four-step approach was used to develop and validate the predictive models. First, the cohort was randomly divided into a training/ derivation sample including 80% of infants, and a validation sample including 20% of infants. Random forests, a supervised machine learning technique, was then applied to the derivation sample to rank candidate variables of importance. 15  The predictive model was evaluated using the c-statistic, performance parameters of sensitivity, specificity, positive predictive value, and negative predictive value, Brier score, 16 Table 2). The Brier score of the models ranged from 0.0385 to 0.0387. In general, the observed and predicted risks were close to each other, (Figure 1), where predicted risks are within the T A B L E 1 Multivariable predictive model of risk of readmission within 7 days after birth hospitalization in late preterm infants (derivation sample, n = 97,611)

| Strength and limitations
Our predictive model is novel due to its focus on LPTs, early Collinearity is often raised as a potential limitation in regression models for prediction. In our study we decided to include both gestational age and birthweight, as there were no large indications of collinearity (based on standard error and variance of inflation factor) and both variables were ranked as important by the random forests.

| Interpretation
LPTs, though more vulnerable to morbidity, mortality, and readmission, often receive similar care to term infants at birth hospitalization. The risk classification strategy developed in our study provides a promising start for future predictive studies and the ability to differentiate LPTs at risk of early readmission. LPTs that had short length of stay, born via assisted vaginal birth, to primipara women, and those who have diabetes need extra attention at predischarge care including assessing parental readiness, screening for hyperbilirubinemia, feeding support, and early follow-up. The protective effect of cesarean delivery is possibly mediated by prolonged birth hospitalization of mother-baby dyad and management of complications such as temperature instability, feeding difficulties, sepsis, and hyperbilirubinemia predischarge. 7 Earlier studies have found that infants ≥36 weeks' gestation who had excess weight loss (≥10% of birthweight) tended to have increased outpatient and inpatient health care utilization in the first month of life as compared to those who had <8% of birthweight loss, 19 similarly dehydration and feeding difficulties are important predictors to early readmission, as is parental readiness. [20][21][22] Inclusion of these variables to the model might improve performance. Neonatal Outcomes." The funding source was not involved in the study design; analysis, and interpretation of data; writing of the report; and the decision to submit the report for publication.

DATA AVAILABILITY STATEMENT
The source of data is the California Office of Statewide Health Planning and Development and California Vital Statistics.
F I G U R E 1 Risk score to predict 7-day readmission in late preterm infants in California. Predicted risk of readmission plotted against risk scores in the validation sample (n = 24,403); bars indicate proportion of late preterm infants by risk score; blue line indicates predicted readmission risk, color codes signify risk category (blue = protective, yellow = neutral, red = at risk).

SUPPORTING INFORMATION
Additional supporting information can be found online in the Supporting Information section at the end of this article.